Innovative Projects Realized

Explore thousands of successful projects resulting from collaboration between organizations and post-secondary talent.

13270 Completed Projects

1072
AB
2795
BC
430
MB
106
NF
348
SK
4184
ON
2671
QC
43
PE
209
NB
474
NS

Projects by Category

10%
Computer science
9%
Engineering
1%
Engineering - biomedical
4%
Engineering - chemical / biological

Use of Mobile ADCPs towards 4-D flow mapping at the FORCE tidal stream site

The complex, turbulent features of fast-flowing tidal currents at the FORCE tidal energy site in Minas Passage make it difficult to accurately measure, model and predict the hydrographic features of the flow. But, these flow predictions are critical to effectively assessing the impact of tidal stream energy on marine life. This project aims to improve the understanding eddies, waves, wakes and other flow features at the FORCE site. Working with members of Acadia and Dalhousie as well as community rightsholders, the project will integrate data from a suite of measurement devices, including acoustic receivers and marine radar data, to map the tidal flow in four-dimensions. The result will be a flow atlas that can be correlated to studies of marine life and used to develop fish-turbine encounter models.

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Faculty Supervisor:

Richard Karsten;Alex Hay

Student:

Lilli Enders

Partner:

Fundy Ocean Research Center for Energy

Discipline:

Statistics / Actuarial sciences

Sector:

Professional, scientific and technical services

University:

Program:

Delineation of Soil Management Zones for Subsoiling to Mitigate Soil Compaction Effects on Soil Properties and to Optimize Crop Yield

The proposed research investigates an opportunity of monitor, measure, and model the role of carbon sequestration and emission of carbon dioxide from agricultural soils of Atlantic Canada. Precision agricultural practices will be designed to promote sustainable agriculture in Atlantic Canada.

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Faculty Supervisor:

Aitazaz Farooque

Student:

Junaid Maqsood

Partner:

Prince Edward Island Potato Board

Discipline:

Engineering

Sector:

Professional, scientific and technical services

University:

University of Prince Edward Island

Program:

Accelerate

Physiological Data Analysis and Credibility Assessment

The subject of assessing credibility is not new. What we are proposing in this project, on the other hand, is novel. It has been shown in various context that assessing credibility is extremely difficulty. In this project, we take a data-driven approach, relying on fundamental knowledge of neural physiology and data collected by NuraLogix, our industrial partner. The idea is simple, lying is stressful and it triggers uncontrollable neural activities that lead to subtle changes in physiological processes, which can be measured and analysed. Working with scientists at NuraLogix, we aim to address the following question: How to improve the performance of current analytic methodologies and detection methods by using newly developed techniques such as machine learning? The outcome of this project could lead to the development reliable algorithms that can be integrated into existing tools developed by NuraLogix but also new insights into this fascinating area.

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Faculty Supervisor:

Huaxiong Huang;Arvind Gupta

Student:

Kian-Chuan Ong

Partner:

NuraLogix Corporation

Discipline:

Statistics / Actuarial sciences

Sector:

Professional, scientific and technical services

University:

Program:

Accelerate

Development of an efficient coding for CDMA-based passive RFID tags

Radio frequency identification (RFID) is a technology that uses radio frequency to identify and track tags attached to objects. This technology is employed in different industries such as asset tracking, supply chain management, ID badging, etc. Current solutions for object tracking have limited precision, suffer from low performance, and are expensive and complex. In this project, by implementing a technology called code division multiple access (CDMA), we improve the RFID system performance significantly. The Aveer CDMA-based RFID system with passive, small, and low-cost tags is able to perform real-time 3-dimensional tracking with micrometer accuracy. These capabilities make Aveer tags applicable to many other technologies such as automation and robotics (e.g., monitoring robotic arms movements that can improve product quality and reduce production cycle time), motion capture (e.g., placing small tags on actors and capture real-time motion with high accuracy), etc.

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Faculty Supervisor:

Reza Soleymani

Student:

Maryam Miriestahbanati

Partner:

TandemLaunch Technologies Inc.

Discipline:

Engineering - computer / electrical

Sector:

Professional, scientific and technical services

University:

Concordia University

Program:

Accelerate

Beneficial Reuse of Sulphur Impacted Soils to Remediate Cement and Concrete Contaminated Sites

This project will use contaminated soils from two types of contaminated sites and combine them, resulting in the soils “treating” each other. The first type of soil used is sulphur contaminated soils, which are created near sulphur stockpiles on industrial oil and gas sites. The second type of soil being treated is cement and concrete contaminated soil, which is created on sites where large amount of concrete are produced and stored over long timeframes. One of the primary concerns with concrete contaminated soils is high pH, which can be lowered by sulphur. Under the correct conditions in soil, sulphur will undergo a biological reaction which causes lowering of pH. Therefore, by mixing these soil types and controlling site conditions, the sulphur contaminated soils can treat the high pH concrete contaminated soils. Additionally, this project will investigate other co-contaminants that often accompany the soils used, to ensure that the process is safe to use. The successful completion of this project will allow the cleaning of one type of contaminated site with the waste from another contaminated site.

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Faculty Supervisor:

Cathy Ryan

Student:

Jordan Hollman

Partner:

Remington Development Corporation

Discipline:

Geography / Geology / Earth science

Sector:

Professional, scientific and technical services

University:

University of Calgary

Program:

Accelerate

Advanced Image-guided Therapy Software for Image-guided Focused Ultrasound Research with Integrated Data Curation for Machine Learning and Artificial Intelligence

Focused Ultrasound (FUS) is a therapeutic modality that can concentrate mechanical energy far from its source in just a few cubic millimetres. There is a significant number of studies investigating the use of FUS as a therapeutic option for multiples diseases, with an emphasis on oncology and brain disorders. While machine learning (ML) and artificial intelligence (AI) are becoming compelling research tools in many areas, the use of ML+AI has remained elusive for FUS research. In collaboration with the company FUS Instruments (Toronto, ON), the goal of this research is to expand the capabilities of our software platform for the control of FUS devices to integrate highly curated data collection, which is fundamental for an effective ML+AI processing, and also to improve the quality of FUS based experimentation. We will also adapt our Proteus platform to drive the RK300 Magnetic Resonance image (MRI)-guided FUS (MRgFUS) system from FUS Instruments.

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Faculty Supervisor:

Samuel Pichardo

Student:

Aidan Johnson

Partner:

FUS Instruments

Discipline:

Engineering - computer / electrical

Sector:

Manufacturing

University:

University of Calgary

Program:

Accelerate

Investigation of IL-5R? expression on ILC2 as a target for Benralizumab

A newly identified group of cells termed type 2 innate lymphoid cells (ILC2s) have been discovered in the past decade. Increasing evidence supports the view that ILC2s play a central role in driving the cellular changes in the airways of asthmatic subjects. ILC2s are increased in severe asthmatics with uncontrolled inflammation despite being on the highest doses of accepted therapies like oral and inhaled steroids. Finding pathways that control ILC2s may provide additional therapies to control severe asthma. We have previously detected a receptor on the surface of ILC2 termed IL-5Ralpha (CD125) and this study aims to confirm the presence of this receptor on ILC2s and understand the biology of this receptor, specifically factors that up-regulate expression levels. In addition, using in vitro culture experiments, we will investigate the effect of a drug that targets and removes cells that express this receptor, namely Benralizumab on ILC2s.

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Faculty Supervisor:

Roma Sehmi

Student:

Xiaotian Ju;Akimichi Nagashima

Partner:

AstraZeneca

Discipline:

Medicine

Sector:

University:

McMaster University

Program:

Accelerate

Optimal Design and Performance Analysis of Building Level Microgrids with Battery Energy Storage

In order to accelerate the transition of our electricity system to renewable sources, it is important that buildings participate effectively as distributed generators. However, traditional integration methods for solar energy often add complexity to our electricity system. With the rapidly declining costs of battery systems, building-level microgrids are becoming a viable alternative allowing buildings to generate and use renewable energy locally rather than exporting to the grid, enhancing the resilience of energy supply and improving demand profiles. The proposed work is to develop an optimization methodology to minimize the cost of energy provided by a building-level microgrid. The optimization will be applied to a set of case study buildings in order to assess the benefits of the microgrid on building performance measures including greenhouse gas emissions and grid integration indicators. This work contributes important insights to the overall smart building ecosystem being developed by WZMH Architects.

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Faculty Supervisor:

Alan Fung;Kristiina Valter Mai

Student:

Jeremy Lytle

Partner:

WZMH Architects

Discipline:

Engineering - mechanical

Sector:

Professional, scientific and technical services

University:

Ryerson University

Program:

Accelerate

Drivers and early warning signs of biodiversity change in urban ecosystems

With increasingly urban populations worldwide and a growing need to ensure ecosystem service provision, managers must plan not only for the urban woodlands we have today, but also for what they might become. This project will develop indicators to detect changes urban woodland succession and its repercussions on future biodiversity. Using existing environmental monitoring data from the Greater Toronto Area, we will first identify candidate woodland characteristics that are sensitive to urbanization, then test their ability to predict woodland succession and biodiversity for a long-term monitoring dataset in the same area. The partner organization will benefit from this work by being able to include expected ecosystem trajectory into their site characterization and conservation prioritization process, helping achieve future ecosystem services and biodiversity targets and improve urban sustainability.

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Faculty Supervisor:

Marc W. Cadotte

Student:

Françoise Cardou

Partner:

Toronto and Region Conservation Authority

Discipline:

Biology

Sector:

University:

Program:

Accelerate

Complementary and competitive interactions between wild and managed bees – Year two

A diversity of native bee species inhabit agricultural and urban landscapes and can be more effective pollinators than the widely employed European honey bee. However, honey and wild bee communities often overlap, which means these bees compete for the same floral resources. Studies of competition between wild and managed pollinators are limited due to methodological constraints. This restricts our ability to predict how pollination and bee diversity will be affected by changes in pollinator community composition. The overall objective of this project is to assess the influence of honey bee density on native bee diversity and pollination across agricultural and urban systems. First, I will determine the optimal number of native and managed bees for crop pollination and production in apple agroecosystems, using an innovative pollination measurement technique and bee diversity experiments. Second, I will assess the effect of honey bee overpopulation on native bee diversity in urban settings, using bee diversity surveys conducted before and after an influx of honey bees to the Island of Montréal. The results of this work will provide the empirical data needed to create alternative crop pollination plans, and form evidence-based beekeeping regulations that are supportive of wild pollinator conservation in crops and cities.

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Faculty Supervisor:

Carly Ziter

Student:

Gail MacInnis

Partner:

Bayer CropScience Canada

Discipline:

Biology

Sector:

Manufacturing

University:

Concordia University

Program:

Elevate

Diversity and Abundance of Beneficial and Pest Insects in Canadian Prairie Agroecosystems – Year two

The proposed research project will assess the insect fauna present associated with prairie wetlands, as well as those found in adjacent fields of crop plants (canola, barley, wheat) and restored grasslands. Insects will be collected using various trapping methods to sample taxa exhibiting different lifestyles. Collected specimens will be identified as specifically as possible to determine taxa found in sampled habitats. This will provide information regarding species diversity and richness of insects in prairie wetlands, which act as nutrition for the waterfowl that Ducks Unlimited are focused on protecting. This information can further be used to assess the ecological health of habitats where Canadian waterfowl exist, as well as determine if beneficial or pest insects may be present in the vegetation surrounding those wetlands which may be affecting local waterfowl or other types of animals, or which may exert an effect on the croplands that prairie potholes exists in.

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Faculty Supervisor:

Sean Michael Prager

Student:

Adam Robert John Jewiss-Gaines

Partner:

Ducks Unlimited Canada

Discipline:

Forestry

Sector:

University:

University of Saskatchewan

Program:

Elevate

Using/An application (with) Artificial Intelligence in Telemedicine and Telehealth

There is a fact that over the last decades life expectation is increased, and human nation is experiencing a longer life span. The idea is to utilize technology in a way that people (senior or patients) can stay at their own home with less care facilities and less life quality degradation with less third-party assistance. In this research, I will be conducting a series of researches in which I can model seniors’/patients’ behavior while they are home so we can have a better insight from their behavior, their patterns/trends of their habits. Internet of things (IoT), artificial intelligence, machine learning and deep learning are main technologies in general which will be adopted to provide the research that I pursue. Data collection, data pre-processing and creating some models based on the collected data sets and training those models to a certain level will give us more in-depth insight from seniors or patients behavior or after hospital care plan.

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Faculty Supervisor:

Bill Robertson

Student:

Ali Asgharzad Hamidi

Partner:

Halitech IT solutions

Discipline:

Engineering

Sector:

Professional, scientific and technical services

University:

Dalhousie University

Program:

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